AI Trends 2024: Machine Learning & Deep Learning with Thomas Dietterich - #666
Published:Jan 8, 2024 16:50
•1 min read
•Practical AI
Analysis
This article from Practical AI discusses AI trends in 2024, focusing on a conversation with Thomas Dietterich, a distinguished professor emeritus. The discussion centers on Large Language Models (LLMs), covering topics like monolithic vs. modular architectures, hallucinations, uncertainty quantification (UQ), and Retrieval-Augmented Generation (RAG). The article highlights current research and use cases related to LLMs. It also includes Dietterich's predictions for the year and advice for newcomers to the field. The show notes are available at twimlai.com/go/666.
Key Takeaways
- •The article discusses current research and use cases of Large Language Models (LLMs).
- •Key topics include monolithic vs. modular architectures, hallucinations, uncertainty quantification (UQ), and Retrieval-Augmented Generation (RAG).
- •The article provides insights into future trends and advice for those new to the field of AI.
Reference
“Lastly, don’t miss Tom’s predictions on what he foresees happening this year as well as his words of encouragement for those new to the field.”